Inverse problem for Orthogonal POlynomials

In summary, the orthogonality condition is satisfied, and so we have a function which is the scaled measure of the even polynomial P_2n(x).
  • #1
zetafunction
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0
given a set of orthogonal polynomials

[tex] \int_{-\infty}^{\infty}dx P_{m} (x) P_{n} (x) w(x) = \delta _{m,n} [/tex]

the measure is EVEN and positive, so all the polynomials will be even or odd

my question is if we suppose that for n-->oo

[tex] \frac{ P_{2n} (x)}{P_{2n}(0)}= f(x) [/tex]

for a known function f(x) can we recover the measure ??
 
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  • #2
We must consider the possibility of different measures leading to the same f(x), as the limiting process for P_2n(x) doesn't involve the measure.
 
  • #3
For example if you quadruple w(x), this results in each polynomial being halved. But halving P(x) and P(0) has no effect on f(x). So right off the bat you're stuck to getting a scaled measure at best.
 
  • #4
If you know

[tex]\lim_{n \rightarrow \infty} \frac{P_{2n}(x)}{P_{2n}(0)} = f(x),[/tex]
then do you not know the even polynomials themselves, up to scaling? Let [itex]P_{2n}(0) = 1[/itex] for simplicity. Then,

[tex]P_{2n}(x) = \sum_{k = 0}^n a_{2k} x^{2k},[/tex]
so if we take the limit as n goes to infinity we have

[tex]\lim_{n \rightarrow \infty} P_{2n}(x) = \sum_{k=0}^\infty a_{2k} x^{2k} = f(x),[/tex]
which basically is just a Taylor series for f(x). Hence we can identify

[tex]a_{2k} = \frac{1}{(2k)!} \left.\frac{d^{2k}}{dx^{2k}} f(x) \right|_{x = 0}.[/tex]
Thus, since we know f(x), we know [itex]P_{2n}(x)[/itex], at least in principle. (Finding a pattern for the derivatives may be difficult).

Since we know the even polynomials, we can in principle discover a differential equation which they solve. This will presumably turn out to be a Sturm-Liouville equation, which one can then use to find out the orthogonality condition, and hence the function w(x) (up to an overall scaling factor set by the choice of [itex]P_{2n}(0)[/itex].

Anything obviously wrong with this procedure, in principle?
 
Last edited:

1. What is an inverse problem for orthogonal polynomials?

An inverse problem for orthogonal polynomials involves finding the coefficients of a polynomial given its orthogonal basis and the inner product of the basis functions. This is the reverse of the usual process of finding the orthogonal basis for a given polynomial.

2. What are orthogonal polynomials?

Orthogonal polynomials are a special type of polynomial where the inner product of any two distinct polynomials in the set is equal to 0. Examples of orthogonal polynomials include Legendre polynomials and Chebyshev polynomials.

3. Why are orthogonal polynomials important in mathematics?

Orthogonal polynomials have many applications in mathematics, including in numerical integration, signal processing, and solving differential equations. They also have a rich history and have been studied extensively by mathematicians.

4. Can the inverse problem for orthogonal polynomials be solved analytically?

In most cases, the inverse problem for orthogonal polynomials cannot be solved analytically. However, there are numerical methods and algorithms that can be used to approximate the coefficients of a polynomial given its orthogonal basis and inner product.

5. What are some real-world applications of the inverse problem for orthogonal polynomials?

The inverse problem for orthogonal polynomials has applications in fields such as physics, engineering, and finance. It can be used to analyze data, solve optimization problems, and model physical phenomena. For example, Chebyshev polynomials are used to approximate solutions to differential equations in fluid dynamics and electromagnetism.

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